Vibration Suppression Trajectory Planning of Flexible Manipulator Based on Hierarchical Self-Adjusting Constrained Optimization

For the vibration suppression trajectory planning of a flexible manipulator, it is difficult to balance the convergence speed and accuracy of the optimization algorithm, resulting in unsatisfactory vibration suppression effects. To do this, a vibration suppression trajectory planning method is proposed based on a novel hierarchical self-adjusting constrained optimization algorithm. First, with the help of a predefined fifth-order polynomial function, the vibration suppression trajectory planning is transformed into a constrained numerical optimization problem characterized by the end elastic displacement, the end residual vibration displacement, and the deviation between the reference trajectory and the candidate trajectory. Furthermore, a novel hierarchical self-adjusting constrained optimization algorithm is designed for the above problems. Its advantage lies in the adaptive adjustment of the evolutionary process through successive enhance of adaptive population size adjustment, hierarchical evolution based on constraint criteria, and self-adjustment of weighted control parameters, thereby better balancing convergence speed and accuracy. Comparative experiments with advanced methods verify the effectiveness and advancement of the proposed method.